Robust radial distortion from a single image

Authors:
Faisal Bukhari;Matthew N. Dailey
Affiliations:
Computer Science and Information Management, Asian Institute of Technology, Pathumthani, Thailand;Computer Science and Information Management, Asian Institute of Technology, Pathumthani, Thailand
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Year:
2010

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Abstract

Many computer vision algorithms rely on the assumption of the pinhole camera model, but lens distortion with off-the-shelf cameras is significant enough to violate this assumption. Many methods for radial distortion estimation have been proposed, but they all have limitations. Robust automatic radial distortion estimation from a single natural image would be extremely useful for some applications. We propose a new method for radial distortion estimation based on the plumb-line approach. The method works from a single image and does not require a special calibration pattern. It is based on Fitzgibbon's division model, robust estimation of circular arcs, and robust estimation of distortion parameters. In a series of experiments on synthetic and real images, we demonstrate the method's ability to accurately identify distortion parameters and remove radial distortion from images.